Construction and validation of an anoikis-related long non-coding RNA-based prognostic model for head and neck squamous cell carcinoma.

IF 1.7 4区医学 Q4 ONCOLOGY

Translational cancer research Pub Date : 2025-07-30 Epub Date: 2025-07-25 DOI:10.21037/tcr-2024-2520

Sijie Yuan, Ziyu Zhai, Yixu Wang, Jilin Peng, Yinghui Ding, Kun Zhao, Xiaodan Zhu, Yuan Zhang, Ling Li, Fanglei Ye, Le Wang

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引用次数: 0

Abstract

Background: As a unique form of apoptosis, anoikis significantly influences tumor biology. Studies have revealed the diverse roles of long non-coding RNAs (lncRNAs) in cancer signaling pathways; however, the prognostic significance of anoikis-related long non-coding RNAs (ARLncs) in head and neck squamous cell carcinoma (HNSCC) remains unexplored. Therefore, this research was undertaken to establish a risk model and assess its predictive ability for prognosis and immune landscape in individuals with HNSCC.

Methods: Data on HNSCC were retrieved from The Cancer Genome Atlas (TCGA). Anoikis-associated genes were acquired from GeneCards, followed by identification of ARLxncs using Pearson correlation analysis. A total of 268 ARLncs from HNSCC samples were extracted from TCGA, and highly relevant ARLncs were identified using Pearson analysis. These ARLncs were subjected to comprehensive bioinformatics analyses, including univariate Cox regression and least absolute shrinkage and selection operator analyses, and an overall survival (OS)-score and OS-signature were generated.

Results: Based on the risk score, patients with HNSCC were stratified into high- and low-risk subgroups to assess the differences in pathway enrichment, prognosis, immune infiltration level, tumor mutation burden, and drug susceptibility. TCGA-HNSCC samples were divided into two subtypes (clusters 1 and 2), with patients in cluster 2 exhibiting worse prognosis and higher levels of tumor-infiltrating lymphocytes (TILs) than patients in cluster 1. Subsequently, we constructed a valid prognostic risk model comprising 12 ARLncs in HNSCC that demonstrated efficacy in predicting prognosis. Patients with high-risk scores exhibited significantly worse OS, lower numbers of TILs, and lower sensitivity to chemotherapy drugs than patients with low-risk scores.

Conclusions: Overall, we successfully established a novel prognostic model based on ARLncs, which holds significant promise for predicting prognosis and personalized therapy for patients with HNSCC.

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基于气味相关的长链非编码rna的头颈部鳞状细胞癌预后模型的构建与验证。

背景：anoikis作为一种独特的细胞凋亡形式，对肿瘤生物学有重要影响。研究揭示了长链非编码rna （lncRNAs）在癌症信号通路中的多种作用；然而，气味相关的长链非编码rna （ARLncs）在头颈部鳞状细胞癌（HNSCC）中的预后意义尚不清楚。因此，本研究旨在建立一个风险模型，并评估其对HNSCC患者预后和免疫景观的预测能力。方法：从癌症基因组图谱（TCGA）中检索HNSCC的数据。从GeneCards中获得嗜酒症相关基因，随后使用Pearson相关分析鉴定ARLxncs。从TCGA中提取HNSCC样本共268个ARLncs，并通过Pearson分析鉴定出高度相关的ARLncs。对这些ARLncs进行全面的生物信息学分析，包括单变量Cox回归、最小绝对收缩和选择算子分析，并生成总生存（OS）评分和OS特征。结果：以风险评分为基础，将HNSCC患者分为高危亚组和低危亚组，评估其在通路富集、预后、免疫浸润水平、肿瘤突变负担、药物敏感性等方面的差异。TCGA-HNSCC样本分为2个亚型（1和2类），2类患者预后较差，肿瘤浸润淋巴细胞（til）水平高于1类患者。随后，我们构建了一个有效的预后风险模型，该模型包含了HNSCC中12个具有预测预后功效的ARLncs。与低风险评分的患者相比，高风险评分的患者表现出更差的OS、更低的TILs数量和更低的化疗药物敏感性。结论：总体而言，我们成功建立了一种基于ARLncs的新型预后模型，该模型对HNSCC患者的预后预测和个性化治疗具有重要意义。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Translational cancer research ONCOLOGY-

CiteScore

2.10

自引率

0.00%

发文量

252

期刊介绍： Translational Cancer Research (Transl Cancer Res TCR; Print ISSN: 2218-676X; Online ISSN 2219-6803; http://tcr.amegroups.com/) is an Open Access, peer-reviewed journal, indexed in Science Citation Index Expanded (SCIE). TCR publishes laboratory studies of novel therapeutic interventions as well as clinical trials which evaluate new treatment paradigms for cancer; results of novel research investigations which bridge the laboratory and clinical settings including risk assessment, cellular and molecular characterization, prevention, detection, diagnosis and treatment of human cancers with the overall goal of improving the clinical care of cancer patients. The focus of TCR is original, peer-reviewed, science-based research that successfully advances clinical medicine toward the goal of improving patients'' quality of life. The editors and an international advisory group of scientists and clinician-scientists as well as other experts will hold TCR articles to the high-quality standards. We accept Original Articles as well as Review Articles, Editorials and Brief Articles.